ArticleBMC infectious diseases2024
Rate and predictors of loss to follow-up in HIV care in a low-resource setting: analyzing critical risk periods.
Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Incidence of loss to follow‑up among East African adults on antiretroviral therapy: a systematic review and meta‑analysis.Systematic reviews · 2025Pooled it
- Large language model-based triage to identify antiretroviral therapy adherence barriers and risk levels in patient messages.JAMIA open · 2026Article
- Incidence and predictors of lost to follow-up in "test and treat era" among adults on ART in Eastern Ethiopia: a retrospective follow-up study.BMC infectious diseases · 2026Article
- Predictors of HIV treatment interruption among people living with HIV in 6 regions in Ghana: a retrospective cohort study.BMC public health · 2026Article
- Engagement trajectories and multilevel influences on retention among adult males with advanced HIV disease in Eswatini: a mixed-methods study.Frontiers in public health · 2026Article
- Trends in advanced HIV disease, treatment interruption, and viraemia in KwaZulu-Natal, South Africa.PLOS global public health · 2026Article
- Virological failure and risk factors among people living with HIV taking second-line ART in Addis Ababa, Ethiopia.PloS one · 2026Article
- The loss to follow-up of participants excluded from the NAMSAL trial: a retrospective cohort study.Scientific reports · 2025Article
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3 authors.
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Abstract
backgroundPatient loss-to-follow-up (LTFU) in HIV care is a major challenge, especially in low-resource settings. Although the literature has focused on the total rate at which patients disengage from care, it has not sufficiently examined the specific risk periods during which patients are most likely to disengage from care. By addressing this gap, researchers and healthcare providers can develop more targeted interventions to improve patient engagement in HIV care.
methodsWe conducted a retrospective cohort study on newly enrolled adult HIV patients at seven randomly selected high-volume health facilities in Ethiopia from May 2022 to April 2024. Data analysis was performed using SPSS version 26, with a focus on the incidence rate of LTFU during the critical risk periods. Cumulative hazard analysis was used to compare event distributions, whereas a Poisson regression model was used to identify factors predicting LTFU, with statistical significance set at p < 0.05.
resultsThe analysis included 737 individuals newly enrolled in HIV care; 165 participants (22.4%, 95% CI: 19.5-25.2) were LTFU by the end of two years, of which 50.1% occurred within the first 6 months, 29.7% within 7-12 months, and 19.4% from 13 to 24 months on ART. The overall incidence rate of LTFU was 18.3 per 1,000 PMO (95% CI: 15.9-20.6), with rates of 167.7 in the first 6 months, 55.4 in 7-12 months, and 18.1 in 13-24 months. Incomplete addresses lacking a phone number or location information (IRR: 1.61; 95% CI: 1.14, 2.27) and poor adherence (IRR: 1.78; 95% CI: 1.28, 2.48) were factors predicting the incidence rate of LTFU.
conclusionLTFU peaked in the first 6 months, accounting for approximately half of total losses, remained elevated from months 7-12, and stabilized after the first year of HIV care and treatment. Address information and adherence were predictors of LTFU. To effectively minimize LTFU, efforts should focus on intensive support during the first six months of care, followed by sustained efforts and monitoring in the next six months. Our findings highlight a critical period for targeted interventions to reduce LTFU in HIV care.
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